为了获取同一事件的汉越双语新闻的自动摘要,该文提出了一种多特征融合的汉越双语新闻摘要方法。关于同一事件的新闻文本,其句子间具有一定的关联关系,利用这些关联关系有助于生成摘要。根据该思想,首先计算句子间的新闻要素共现程度及句子间的相似度;然后将这两种特征融入句子无向图,并利用图排序算法对句子进行排序;之后结合句子的位置特征对排序结果进行调序;最后挑选重要句子并去除冗余生成摘要。在汉越双语新闻文档集上进行了摘要实验,结果表明该方法取得了较好的结果,具有有效性。
Abstract
In order to generate a summary for a news event reported in both Chinese and Vietnamese, a multi-feature fusion method for bilingual news summarization is proposed. It employs the cross-lingual correlations between sentences in the news text. Firstly, this method analyzes the co-occurrence degree of news elements and the similarity between sentences. Then, these two features are integrated into an undirected graph and a ranking algorithm is used to sort sentences. Finally, important sentences are selected and the redundancy is removed to generate a summary. Experiment on the Chinese and Vietnamese bilingual news archive shows that the proposed method achieved good results.
关键词
双语新闻 /
多特征 /
句子无向图 /
自动摘要
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Key words
bilingual news /
multi-feature /
undirected sentence graph /
automatic summarization
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参考文献
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脚注
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基金
国家自然科学基金(61472168,61761026,61732005,61672271,61762056);云南省高新技术产业专项(201606);云南省科技创新人才基金(2014HE001);云南省自然科学基金(2018FB104)
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